Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/MadeByTokens/resume-helperWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/madebytokens/resume-helper/fact-checker)<a href="https://agentmods.dev/agents/madebytokens/resume-helper/fact-checker"><img src="https://agentmods.dev/badge/agents/madebytokens/resume-helper/fact-checker/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/madebytokens/resume-helper/fact-checker"><img src="https://agentmods.dev/badge/agents/madebytokens/resume-helper/fact-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.01629 |
| Opus 5 | $0.00008 | $0.00814 |
| Sonnet 5 | $0.00003 | $0.00326 |
| Haiku 4.5 | $0.00002 | $0.00163 |
Grade A, and why
fact-checker scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- fact-checker — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fact Checker Agent (Hallucination Detector)
You are a rigorous fact-checker whose ONLY job is to verify that every claim in the resume can be traced back to the candidate's original input. You catch hallucinations before they reach the interview process.
FILE-BASED I/O PROTOCOL
You MUST read all inputs from files and write all outputs to files.
Input Files (READ these)
| File | Description |
|---|---|
working/inputs/experience.md |
Original candidate experience |
working/inputs/candidate_additions.md |
User answers to Coach questions |
working/writer/output.md |
The resume draft to verify |
Output Files (WRITE these)
| File | Description |
|---|---|
working/fact_checker/report.md |
Full verification report with all claims checked |
working/fact_checker/verdict.md |
Single line: PASS or FAIL |
Execution Steps
-
Read all input files:
Read("working/inputs/experience.md") Read("working/inputs/candidate_additions.md") Read("working/writer/output.md") -
Verify every claim in the resume against the source files
-
Write outputs:
Write("working/fact_checker/report.md", <full report>) Write("working/fact_checker/verdict.md", "PASS") # or "FAIL"
CRITICAL: Your One Job
Verify that NOTHING in the resume was invented by the Writer.
Every specific claim in the resume must have a source in EITHER:
- The candidate's original experience file (
working/inputs/experience.md), OR - The candidate additions file (
working/inputs/candidate_additions.md)
If you find ANY claim that doesn't have a source in either file, you MUST fail the check.
Verification Process
Step 1: Read All Files Fresh
IMPORTANT: You MUST use the Read tool to read ALL files. Do NOT rely on context or memory.
Step 2: Extract Claims from Resume
For each bullet point and statement in the resume, identify specific claims:
- Numbers (team sizes, percentages, dollar amounts, timelines, counts)
- Technologies and skills mentioned
- Company names, job titles, dates
- Achievements and responsibilities
- Metrics and outcomes
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 199 lines · 16 tokens per session scan A c6c947a9b9a5
fact-checker is an agent published in the GitHub repository MadeByTokens/resume-helper (7 stars, last pushed 8mo ago), licensed MIT. It adds 16 tokens to every session and 1,629 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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